Ideometrics: a scientific approach to generating, evaluating, and prioritising ideas

TL;DR

Ideometrics is a new scientific approach to generate, evaluate, and prioritize ideas using structured and testable methods.

Contribution

The paper introduces ideometrics as a unified, falsifiable framework for idea generation and evaluation across disciplines.

Findings

Over 70 methodological approaches to idea generation and evaluation were identified and mapped.

Ideometrics integrates diverse traditions through a rigorous empirical framework with testable predictions.

The approach supports AI, statistical inference, and systematic refinement of ideas.

Abstract

This paper introduces and describes a new integrative scientific approach – ideometrics – building on the ‘sense of ideas’ and ‘value of information’ concepts. Ideometrics is the emerging field of generating, evaluating, and prioritising ideas.

Focused on the generation, evaluation and prioritisation of ideas, we identified and then mapped the landscape of methodological approaches that have been used over time, disciplines, and epistemic paradigms across many areas of human enquiry. Although these often appeared to arise independently, isolated by geographical and disciplinary boundaries, they share remarkable conceptual and structural similarities, from creative ideation, balancing of subjective and objective criteria, to iterative refinement. Finally, we sought to integrate these traditions through an empirical scientific framework.

We identified over 70 different methodological approaches. We then proposed several steps to establish ideometrics as a rigorous and practically useful field of science, rather than merely an integrative framework. Ideometrics is falsifiable: it supports testable predictions about future performance of competing ideas, while its methods are increasingly evolving into rigorous, structured, standardised and mathematically characterised tools. It enables accumulation of evidence and progressive refinement of theory, application of statistical inference, and introduction of artificial intelligence (AI).

Future progress will make ideometrics increasingly quantitative, digital, testable and replicable. We therefore foresee assessments of scientific footprints of each of the >70 methodological approaches, developing formal reporting guidelines to standardise ideometrics studies and allow meta-analyses, and conducting empirical comparisons between methods used to address the same challenges. Ideometrics represents an attempt to systematically unify the scientific approaches to generating, evaluating, and prioritising ideas. Its practical application should address scarcity by assisting individuals, institutions, and societies to focus their limited time, energy, capacity and resources on pursuing the ideas that are most likely to achieve their stated aims, based on an objective and scientific approach, rather than subjective and intuitive priority setting.